Things we have done

Semantic Fast-Forward Video

In this project, we deal with a central challenge that is to make egocentric videos watchable. These videos are generally long-running streams with unedited content, which make them boring and visually unpalatable. Just fast-foward it is not enough, because the natural motion of the recorder’s body in a fast-forward mode becomes nauseate. In this work we propose a novel methodology to compose the new fast-forward video by selecting frames based in semantic information extracted from images.